Towards a Theoretical Framework of Autonomous Systems Underpinned by Intelligence and Systems Sciences

Yingxu WANG, Ming HOU, Konstantinos N. PLATANIOTIS, Sam KWONG, Henry LEUNG, Edward TUNSTEL, Imre J. RUDAS, Ljiljana TRAJKOVIC

Research output: Journal PublicationsJournal Article (refereed)peer-review

25 Citations (Scopus)

Abstract

Autonomous systems are an emerging AI technology functioning without human intervention underpinned by the latest advances in intelligence, cognition, computer, and systems sciences. This paper explores the intelligent and mathematical foundations of autonomous systems. It focuses on structural and behavioral properties that constitute the intelligent power of autonomous systems. It explains how system intelligence aggregates from reflexive, imperative, adaptive intelligence to autonomous and cognitive intelligence. A hierarchical intelligence model (HIM) is introduced to elaborate the evolution of human and system intelligence as an inductive process. The properties of system autonomy are formally analyzed towards a wide range of applications in computational intelligence and systems engineering. Emerging paradigms of autonomous systems including brain-inspired systems, cognitive robots, and autonomous knowledge learning systems are described. Advances in autonomous systems will pave a way towards highly intelligent machines for augmenting human capabilities.
Original languageEnglish
Pages (from-to)52-63
JournalIEEE/CAA Journal of Automatica Sinica
Volume8
Issue number1
Early online date28 Oct 2020
DOIs
Publication statusPublished - Jan 2021
Externally publishedYes

Bibliographical note

This work was supported in part by the Department of National Defence’s Innovation for Defence Excellence and Security (IDEaS) Program, Canada, through the Project of AutoDefence: Towards Trustworthy Technologies for Autonomous Human-Machine Systems, NSERC, and the IEEE SMC Society Technical Committee on Brain-Inspired Systems (TC-BCS).

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